The advance of industrial technologies has led to the wide use of computer numerical control machine tools in workpiece production, and the development trend of the next-generation workpiece production is towards unmanned machining and automated production. The higher the degree of automation of a factory, the more the personnel cost in machining process can be saved. However, to ensure the good quality of machined products and the normal operation of production lines, the high-degree automation requires more detection components for detecting the statuses of the production equipment in the manufacturing process as replacing the conventional inspection based on human eyes. The manufacturing of various machine parts is carried out usually by some machining methods, such as milling, drilling and turning. Milling is using a milling machine to hold a metal material on a table and then translate a tool or a cutter in the X axis or the Y axis according to a machining position and spin the tool about the Z axis as the cutter rotation axis relative to such an unfinished workpiece, so that unwanted parts are shaved off from the unfinished workpiece by the upward and downward milling. Considering the enhancement of production capacity, one or more CNC machine instructions may be given to control a cutter to spin for a long time. However, if not all chips are estimated or a wrong machining parameter is used the machining process, the temperature of the tool will increase so that the cutting resistance will increase. In this case, if this abnormal status of the tool is not detected in real time, the lifespan of the machining cutter will reduce or the CNC machine will shut down. Even, when severe wear or a tool fracture occurs on a tool, the product yield rate drops down and thus, the schedule of shipping and the production capacity will be affected.
As aforementioned, the monitoring of cutter status plays a significant role in a machining process. The status of a cutter not only is associated with the cost of the production equipment but also affects the quality of machined products. Both cutter breakage and cutter wear cause the reducing of the product quality. Although some detection methods for directly measuring cutter statuses by laser light, resistances, the optics and air pressures, and some detection method for indirectly estimating cutter statuses by temperatures, vibrations, the engine power or the thermoelectric effect are provided nowadays, these methods requires additional sensors, e.g. laser transceivers, accelerometer, etc. Moreover, sometimes the time for the tool to move away from a respective workpiece may be lengthened in order to satisfy the working conditions of various sensors, and thus, the production efficiency of a machine tool decreases. Further, the installation and maintenance of sensors causes a higher manufacturing cost, and an additional time for repairing or replacing the sensors installed near the tool is also required since they are easily damaged by cut-off chips or cutting fluids. In addition, the monitoring methods of tools usually provide only two statuses indicating the estimated wear level of a respective tool: “Normal! Unnecessary to replace” or “Worn! Necessary to replace.” Without the more detailed determination of tool statuses, an accessible tool having slight wear may be replaced ahead of schedule. This also increases the expenditure on the production equipment.